A Study and Analysis of Machine Learning Algorithms and Its Applications

Authors(2) :-Dr. Archana Sharma, Prof. Vibhakar Mansotra

Machine learning is a subfield of artificial intelligence (AI). Deep understanding of data inputs would help in taking output as optimized decisions and also help them to work in more accurate and in efficient manner. Designing and implementing the algorithm and using it in most appropriate way is, the real challenge for the developers and scientists. Machine learning algorithms allow computers to train inputs data and use statistical analysis for optimum decision values. Based on data inputs, machine learning facilitates computers in building models from dataset in order to get automatic decision-making processes. Today, many technical users has benefitted from machine learning. In this paper, we will discuss the machine learning methods, and explore various algorithmic approaches in machine learning providing with some of the positive and negative attributes of each algorithm and most efficient use to make decisions and complete the task in more optimized form.

Authors and Affiliations

Dr. Archana Sharma
Department of Computer Science, Institute of Management Sciences (IMS), Jammu, Jammu & Kashmir, India
Prof. Vibhakar Mansotra
Department of Computer Sciences and IT, University of Jammu, Jammu, Jammu & Kashmir, India

Artificial Intelligence, Machine Learning, Decision-Making Process, Applications.

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Publication Details

Published in : Volume 4 | Issue 1 | March-April 2018
Date of Publication : 2018-04-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 320-325
Manuscript Number : CSEIT411853
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Dr. Archana Sharma, Prof. Vibhakar Mansotra, "A Study and Analysis of Machine Learning Algorithms and Its Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 1, pp.320-325, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT411853

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